Data Scientist.

    Key Responsibilities

    • Work with engineering and research teams on designing, building and deploying data analysis systems for large data sets.
    • Create/use Machine Learning algorithms to extract information from large data sets for pattern discovery leveraging Apache Spark and MLlib APIs (preferably in Scala or Python).
    • Establish scalable, efficient, automated processes for model development, model validation, model implementation and large scale data analysis.
    • Develop metrics and prototypes that can be used to drive business decisions.
    • Provide thought-leadership and dependable execution on diverse projects.
    • Identify emergent trends and opportunities for future client growth and development.
    • Work with team leaders and members to solve client analytics problems and document results and methodologies.
    • Provide a business metrics for the overall project to show improvements (contribution to the improvement should be monitored initially and over multiple iterations).
    • Provide on-going tracking and monitoring of performance of decision systems and statistical models.
    • Lead the design and deployment of enhancements and fixes to systems as needed.

    Minimum Requirements

    • Bachelor degree in mathematics, statistics or computer science or related field; Master degree preferred.
    • Typically requires 3-5 years of relevant quantitative and qualitative research and analytics experience.
    • Solid knowledge of statistical techniques.
    • The ability to come up with solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.
    • Strong programming skills (such as Scala, Spark, MLlib or other big data frameworks and Python), and statistical modeling (like SAS or R).
    • Experience with common data science toolkits, such as R, Weka, NumPy, MatLab.
    • Experience in data visualization tools like Apache Zeppelin, Tableau.
    • Proficiency in querying languages like Hive, PIG, SQL.
    • Experience in SAP HANA, SAP HANA Vora is highly preferable.
    • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
    • Proficiency in the use of statistical packages.
    • Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.
    • Strong communication and interpersonal skills.
    • Knowledge of one or more business/functional areas.
    • Demonstrable ability to quickly understand new concepts-all the way down to the theorems- and to come out with original solutions to mathematical issues.
    • Good communication and interpersonal skills.
    • Knowledge of one or more business/functional areas

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